This week one thing became abundantly clear, and it has to do with what usually goes unseen.

I’m talking about what’s “under the hood” when it comes to how we work with data for the wine industry. I’m talking about the mechanics and the HOW things get done, that normally don’t get much of the attention.

Except they should. Because that’s the engine that’s driving this whole endeavor.

Things like programming in languages like Python, and storing data in cloud-based data lakes, and the automated processing of data (including the use of machine learning), all in service to accuracy and speed.

Here’s another way to say it: The front end of what we do is still very educational and user-friendly, but the engine behind it has been revved up exponentially.

Google, Microsoft and many other companies are pouring billions of dollars into the development of new intelligent technologies, and we’re early adopters of many of their platforms. Which means that our clients can forego the investment internally and leave the data management in the hands of people who do it all day, every day.

Maybe you’re in the same boat. Or maybe knowing the ins-and-outs of Python and cloud-based data lakes rocks your world. Either way, we all want to know how all of this engineering can help our business.

Let’s talk about it. Drop me a line, and let’s see what we can do together.

Last week I asked for your feedback and input on data sources in the areas of wine and food tourism, in advance of the keynote I’m giving in a few weeks in Cape Town. And boy, did you deliver! It’s incredibly exciting to flesh out the presentation with hands-on learnings from fresh sources and efforts in parts of the world that, frankly, were brand new to me.

So thank you, sincerely.

That example sets the stage perfectly for what I’d like to focus on this week, and it has to do with collaboration.

If we didn’t collaborate, we wouldn’t have a reason to exist.

That’s because the true definition of a big data company is to aggregate multiple sources of data across multiple platforms. For us that means building out an ecosystem of data partners who each deliver raw data that’s useful for our clients. In some cases it’s a winery’s own data that’s one of the sources.

As I said, it’s about collaboration.

In practice, and in a very simplified sense, this is how it works.

Listen to the client. Understand intimately the area of research.

Draft a scope of work.

Iterate the scope, from both sides, in order to extract maximum value and to clarify expectations.

Execute the scope of work.

Enolytics delivers the results, via Webinar or in person

Give the client time to process the results, within their own framework for business and at their own pace.

Client asks follow up questions.

Enolytics responds.

Repeat steps 7 and 8 till the area of scoped research is well understood.

My second (significantly more rational) reaction: That’s actually three questions rolled into one.

How can data about wine help?

How can data about food help?

How can data about tourism help?

What I especially love about the “three in one” factor is that it reflects the true definition of a big data company: to aggregate multiple sources of data across multiple platforms.

In other words, pulling together data about wine + food + tourism is what our team of analysts is specifically skilled at doing.

So yes, we’ve got sources about wine consumers that we can pull from, that they’re already used to dealing with. The data has to do with behavior, and location, and sentiment, and frequency.

And yes, thanks to new friends and local partners, we’ve got additional data about things like hotel/occupancy figures, air arrivals and social media reach.

Which is all good, and really exciting.

But we know there’s more, particularly when we think about the second part of the request for the keynote content: What can South Africa learn from California, particularly as it relates to the tourism industry recovering from a natural disaster?

In California, it was last year’s wildfires and the drought before that. In South Africa, it’s their drought also and reports of a water shortage that has crippled tourism efforts and reservations.

Plenty of similarities, and lots of lessons to be learned.

Here’s my question for you, and our request for your help:

What sources of data do you know, who could contribute to our analysis? Where, in California or elsewhere, can we turn for quantifiable “lessons learned” that are helpful and worth sharing?

We’re open to suggestions, and I’d love to feature the knowledge of these sources in my talk.

Here’s my cell phone number and email: +1.702.528.3717 and cathy@enolytics.com, and I’ll actually be in Sonoma this weekend, all the way until Tuesday, in case you’re local and would like to meet up in person to talk.

I don’t know who said that originally, but it’s been on my mind these past few weeks as I’ve had the chance to see how quantitative data analysis – which is Enolytics’ focus – complements and adds onto qualitative data analysis.

It’s worth taking a moment to pause here, and underscore what this means.

For many decades now, the wine industry has relied on qualitative research, like surveys and focus groups and in-person, face-to-face interviews.

This style of research is incredibly valuable, and it’s grounded in well-established, well-executed social science. There’s a reason why so many research efforts, and so many decisions in our industry have long been based on these methods of analysis.

I respect that. Our team respects that. It’s foundational, and we value the ongoing contributions it makes.

What we also value is that, today, there’s a flip side of the coin, and that’s the quantitative research that is our focus. Big data is possible because of technology, and because millions of consumers around the world are telling us, in an objective way and digitally, what they think and how they feel about wine, every moment of every day.

We respect that too, especially as we continue to grow and explore and are presented with opportunities to see how the quantitative style of analysis can dynamically interact with the qualitative style. How they reflect each other. How they build upon each other. How they differ. Where the breaks are, and what the limitations and advantages are of each side of the break.

Quantitative data, as a first step, could help us to figure out the what: what consumers consider to be your competitive set, for example, and what kind of traction you’re seeing in markets from New York to Chicago to Los Angeles. It helps you to see the problem areas, and also what questions to ask.

Qualitative data, subsequently, could help us to figure out the why: why consumers in Cincinnati are raving about your chardonnay, and why interest in your pinot has dropped in Houston.

Does that make sense?

It’s an exciting intersection of collaboration, and we’re psyched to be part of it. Personally, I’m psyched to share more with you in the coming weeks about the hands-on practicalities of this.

These are opportunities to build bridges between how things have always been done, and how they can be complemented by new layers and common points of engagement.

If you find yourself comfortable in the “how things have always been done” part, we get it. And we aren’t suggesting you abandon it. We are suggesting that there are ways to add on, a step at a time, that can also be within your comfort zone.

Let’s take the first steps. Please be in touch, and let me know what’s on your mind.

That was the most important lesson from my favorite professor in Journalism school. What he meant was, if everyone else is already looking at the story over HERE, then your story -- the opportunity to do something different -- is over THERE.

I've been thinking about that over the Labor Day holiday, when two different articles came across my desk. They're both from the academic world, and they both touch the sweet spot of Enolytics' mission to "fill in" the blindspot of wine consumer behavior and sentiment.

These two articles tell us where most people in the wine industry already zig. (Get ready for the zag, below.)

Two weeks ago Neema Kotonya and Emiliano De Cristofaro of University College London and Paolo De Cristofaro of the Tipicamente wine blog published a paper about wine consumers' social experiences through the lens of the Vivino app.

A graduate student named Marie Schu at Erasmus University in Rotterdam wrote her master's thesis on the wine industry's reactions to consumer use of new media ratings platforms.

What's the zig, according to these resources? As Schu puts it, most of her research subjects "appear to be in denial about the value of contemporary consumer rating practices."

Most wine industry people, in other words, are in denial about how impactful increased consumer digital involvement can be, especially since it brings with it the advantage of increased demand in the marketplace.

That's the zig.

Which means that the zag -- your opportunity right here -- is to capitalize on what most others are looking at, and denying, over there. That consumer usage of digital platforms increases every day. That the potential is already here, and available, and waiting to be tapped into.

What has been the response from someone, one of Enolytics' clients, who has zagged?

Finally consumers are at the center of the strategy. Finally we can base decisions on solid data and not feelings. Finally wine marketers could enjoy a new era where the market needs are clearly identified and proactively managed. Cathy Huyghe and Enolytics has envisioned a new future providing what wine marketers were really missing!

Finally.

Are you ready to seize the opportunity, while others lag behind in denial? Are you ready to zag, while most others zig?

We can help.

Please be in touch, and tell us what you need. And thank you, as always, for reading.

There are a few key moments in every writer’s annual cycle when we pause and take stock.

It varies writer to writer, and certainly we recalibrate on a near-daily basis, depending on current news and developments.

For Enolytics, and the flow of these Enolytics 101 posts, I typically take stock of the "big picture" at three pivot points each year.

At the beginning of December, which is when I look back and reflect

In the middle of January, which is when I look ahead and envision possibilities

At the end of the summer, which is this very sweet spot in between the exhale of vacation and the build up of adrenaline for the busiest season of the year.

Right now, in other words, we’re studying our own analytics around the content that resonated with you the most. We’re getting a read, across all platforms and feedback, on which topics matter to you and where we ought to dig deeper.

Here were the five most popular Enolytics 101 posts so far this year (numbers 1 to 5), along with the five most popular posts from the last four months of last year (numbers 6 to 10). The second half of this list tells us about the seasonality of our content: which topics matter most during our industry’s busiest time of the year.

We’re looking forward to diving back into that season, when we see you back here after Labor Day. As always, thank you for reading.

One of my favorite things to do in this Enolytics 101 series is shine a spotlight on other business and people who are doing impactful, cool things in the wine + data space.

3x3 Insights, based in New York, is one of them and here’s why: they empower independent retailers and, better yet, they empower them in useful, content-rich ways.

Here’s my Q&A with 3x3 Insights, on their use of effective video (“Depletion reports just won’t cut it…”), beverage data in ethnically diverse communities, and where their data comes from.

* * * * *

Why “3x3 Insights”…?

Although our mission is to ultimately to help the independent alcohol retailer compete by using analytics and engagement tools to provide superior customer experience to keep people shopping at their stores, we have always had all three tiers of the industry in mind. In fact, our name is a nod to the three-tier system, as well as a reference to the “last three feet” (which refers to the customer standing at the shelf where they make the decision) that has always been important.

We are in pilot conversations with numerous suppliers on ways we can help them understand and reach their most valuable customers in the markets where we already have stores. We also have been in talks with major distributors on ways we can help each other succeed by extending the reach of our analytics network while providing them superior data and analytics than the depletion data they currently rely on.

I love that you’re using video (your “Retail Untapped” series) to communicate. What drove this decision, and how is it working out so far? What kind of traction are you seeing?

We took a good hard look at how the entire industry develops media and content and realized there was very little innovation in the video sphere. We know that video is a medium that is continuing to grow and can more powerfully capture the attention of independent retailers and the industry as a whole. We wanted to create something well-produced, authentic, and truly informative; something that would actually add value to those who watch. We are focusing on empowering retailers in the independent channel however we can: given the obvious popularity of video and that nobody else was doing it, we developed this bi-weekly video series highlighting important news, trends and insights for the independent alcohol channel.

The response thus far has been outstanding. We have already seen consistent, strong growth across all mediums and distribution channels, including state associations, the ABL, and our own network of influential independent retailers. We’re quickly realizing that the industry needs a strong hub of content focused on news and insights from around the entire independent channel. We’re working hard to make sure we continue to deliver!

One of the reasons I was first attracted to 3x3 Insights was your awareness that diverse ethnic communities were underserved, and not well understood, when it comes to beverage alcohol marketing. How are your efforts going so far?

Demographics and understanding brand performance in diverse segments is important to 3x3 on two dimensions. The first looks at the demographic differences in store and product performance, and consumer buying patterns within neighborhoods in local markets. Our platform algorithmically models the neighborhoods surrounding a store to place it in a particular demographic profile, which allows comparisons between neighborhoods and markets on a demographic basis.

When we launch our consumer engagement and marketing offering to retailers, our data will grow richer in its ability to target demographics at a product and consumer level, which will enable both deeper understanding of the consumer's diversity and engage them appropriately with the brands that resonate.

How do you integrate on-premise and off-premise data?

Today our network consists of off-premise beverage alcohol retailers, but we are moving quickly to incorporate on-premise in fulfillment of 3x3's vision of creating an ecosystem of retailers that help brands put the right products in the right customers' hands through the right experiences. In order to accomplish that vision, our platform needs to be able to understand buying behavior, and move consumers between on- and off-premise buying opportunities.

We utilize several data sources to create a rich understanding of consumer buying behavior. These range from aggregated social media data measuring sentiment for brands, to data that consumers share with us based on their desires to participate in the ecosystem, and the demographic data collected both at the store level and when reported by consumers. We take great care in using consumer data, exceeding the requirements that exist today around consumer privacy. Our aim is to provide a platform that consumers want to benefit from by affiliating with their beloved local, independent retailers and help those retailers battle the effects of Amazonification that come from rampantly personalizing sales and commoditizing products.

* * * * *

So what’s the relationship between 3x3 Insights and Enolytics?

Mutual respect, first of all, for adding value to the industry in our own ways. And, second, deep partnership awareness: each of our inputs is recognized for contributing insights that, when combined, amount to more than what we could contribute alone.

Data + wine is a growth area, and it ramps up more and more each day. None of us – including you – is in this on your own.

How can we help?

I look forward, as always, to your thoughts, and thank you for reading.

This week I’ve been enjoying my first-ever trip to Mexico (not sure how it’s “first-ever” but that’s probably a story for another time) and I’ve picked up a few things about the wine industry here.

There are a heck of a lot of sommeliers in Mexico City. Their popularity and enthusiasm reflect the spiking consumer interest here in wine, and in Mexican wine in particular.

A state called Querétaro, in central Mexico and about a two-hour drive from Mexico City, is fostering a rapidly-expanding wine and food tourism sector. Hand-in-hand with that is an influx of significant foreign investment, which helps to build technologically sophisticated wineries and tasting rooms and adjacent restaurants and cafés.

96% of the 2.1 million cases of wine produced here are consumed here.

Mexican wine accounts for 40 to 45% of all wine consumed in Mexico, and the market is seeing an annual growth rate of 10 to 11%.

Right.

Tomorrow, as part of the México Selection program organized by Concours Mondial de Bruxelles, I’ve been asked to introduce Enolytics and what data analysis can mean in the context of those bullet points, above.

I honestly cannot wait, partly to share some of the insights that have already risen to the surface about wine consumers in Mexico (indirectly even, in the course of other projects) and partly to hear how the audience here receives these insights.

Once we show what’s possible, how do they take the ball and run with it?

If we can locate digital consumer sentiment within the neighborhood of specific restaurants (and we can), how does that help that young, savvy cadre of sommeliers, in Mexico City and elsewhere?

If we can segment consumer sentiment around Spanish wine, relative to French wine, relative to Mexican wine, and then track the trends of that sentiment over time (which is all possible), how does this empower the emerging Mexican wine industry?

If we can take data that’s specific to wine consumers, and then overlay that with data from the tourism sector, how does that help direct valuable resources and communications so that eno- and gastro-tourism continues to thrive?

We dunno. Yet.

But boy are they – are we – hungry to find out.

Let me toss the question to you.

Once you see what’s possible, how will you take the ball and run with it?

I’d love to hear.

Thank you for reading and thank you, as always, for sharing this journey with me.

Sometimes we have them but we don’t get to ask them, and sometimes we don’t know which ones to ask.

Which is why, for this week’s post, I want to address three wine data-related questions that we’ve been hearing repeatedly these past few months. If they’re on the minds of people we actually get to speak to, we think the chances are pretty good that they might be on your mind too.

So let’s get to it.

***

Question: I understand that you work with a winery’s own data, and that you work with third party data from your network of partners. Do the two kinds of data ever overlap, and work together?

Our Answer: We love this question, and the answer is yes. We can work with both sets of data and, actually, it’s one way to extract maximum benefit out of a project.

We love this question because it’s a creative way to merge two styles of data. On one hand you have specific information about your own customers, like their geographic distribution and buying patterns over time. On the other hand you have more general information about wine consumers’ geographic distribution and buying patterns over time. Overlay those two kinds of information, add additional fields like varietal and price point, and you start to see possibilities, such as greater or lesser concentrations of interest for the style of wines you’re selling, and the historical trends for that interest over time.

***

Question: Do you also advise on implementing the results of your analysis?Our Answer: We are equipped to do this, yes.

Candidly, however, it is very much a collaborative effort. When we deliver our findings to a client they appreciate the unbiased and quantified analysis and point of view, but they also see (with some clarity and imagination, I might add) exactly what they need to do with those findings. In fact, they’ve envisioned how to put the findings to work in ways we ourselves hadn’t imagined, simply by virtue of their knowing their business better than anyone else.

That’s the incredibly cool part of opening a new window onto insights that are mostly, until now, unseen.

***

Question: Can you interface with the CRM we already use?

Our Answer: Yes. In most cases we can interface to them out of the box. We have connectors to all Salesforce-based CRMs. We also realize that there are many ways that wineries manage information about their customers. How about those we haven’t yet interfaced with? In most cases, the common denominator is that we’d need the appropriate rights and access to connect. Our engineers are experts at writing the appropriate scripts and implement automation, so that ultimately this becomes a non-issue.

***

Those are a few of the most common questions we’ve heard lately. How about you? What are your questions, and how can we help?

Drop us a line and let us know. Sometimes it’s easiest to schedule a webinar and show some visuals, and we’re game for that too.

Looking forward to your ideas and questions and thank you, as always, for reading –

It’s a major topic around the office these days but, like most of you, I’m not a “data person” and concepts like this are new territory. To get my head around it, I need to have it explained in relation to something that I do know and understand.

Like social media.

Most of us use it most days, right? If we’re also using it at work, particularly to manage the online presence of a wine brand, we’re also likely accessing the analytics dashboards, which tell us things like performance, reach and popularity of each post.

Those analytics, in turn, help us to refine and craft the content of our future posts. Analytics, in other words, enables us to be responsive to our audience.

Makes sense so far.

But what if we could do more than respond to our audience?

What if we could understand that audience so well that we could forecast the kind of content that they’re most likely to “like”?

What if we could put that information to work, and start to steer the audience in favor of our brands?

This is where machine learning comes in.

We could start with this question: How does consumer behavior on social media change over time? How does it change when it comes to wine, and in relation to our brand?

Wouldn’t that be a cool thing to know?

We could, technically, dedicate massive amounts of time and human resources to studying exactly that.

Or we could set the tools of machine learning to work and direct their energy toward analyzing, without our interference or interpretation, a very high volume of data around parameters and filters that we set.

It’s exponentially faster.

It’s more accurate.

It isn’t impacted by subjective interpretation.

It’s a strategic, efficient use of resources.

And you end up with concrete, quantifiable information to work with.

Do I understand the methods?

Nope. As I said above, concepts like machine learning are new territory for me and I’m not about to claim understanding of them in any operational kind of way.

But I’ll tell you what I do understand, is what to do with the results and information that come out the other side.

I bet you would, too.

What can machine learning tell us about your brand?

Let us demonstrate. Just drop me a line and we’ll get the conversation started.

To document every single wine made, all around the world, and warehouse the information in one central location.

(My first reaction: “Wait. What?” Second reaction: “Herculean.” Third reaction: “Sisyphean,” as in, desirable, super labor-intensive, and just out of reach.)

I mean, who does that? And, more importantly, why?

The “who” is David Gluzman and his team at Calgary-based Global Wine Database. GWDB started out, almost as a beta test and along with the help of the Canadian Vintners Association, to successfully execute their vision to document every single wine in their home country of Canada.

They proved it’s possible. More than that, they proved it’s beneficial to the entire Canadian wine industry. You can see the results for yourself here. Prior to the launch of this website, Gluzman said, “the world didn’t truly know all that much about the landscape of Canadian viticulture, like the fact that the country produces more than 130 different grape varieties. Today every winery has access to store and share the facts of what they produce, to the entire world, for free.”

Which brings us to the “why” of this idea.

GWDB’s tagline says it all: “Accurate data, controlled by producers.”

That’s a pretty big clue to what this is all about.

To enable wineries to control the facts that are “out there” about their wines, including vintage-to-vintage variation, updated tech sheets, label shots, and reviews.

You upload the information once, basic details like location, logos and tasting notes. The beauty of the platform is what happens next, and automatically.

Corporate websites that the winery owns are updated, such as the public-facing website and the ecommerce store.

Trade and media websites are updated, which means retailers can go directly to GWDB for the latest technical notes.

Any third-party apps that are integrated with GWDB are updated, which makes it that much easier to stay on top of the information consumers see when they pull up your wine in apps like Vivino and Delectable.

The cycle repeats itself whenever new information, like the next vintage, is uploaded.

Data people can geek out, pretty far, about the technology that enables all of this to happen. Because it’s impressive.

The takeaway for everyone else is that bit about wineries themselves presenting, accurately, the information that’s circulating about their wines.

Think about what happens when you search for a movie on Google. You can find out almost everything about it, like who produced it, the actors, the writers and so much more. When you do the same for wine, however, the data is incredibly fragmented or non-existent.

“We’re providing a platform to allow third parties to integrate into accurate wine data,” Gluzman said. “Future technology – from Augmented Reality to Artificial Intelligence to Blockchain – all depend on data. The wineries have it, but they don’t have a place to put it for the world to access. That’s us.”

Word.

Not sure about you, but learning about GWDB has set my mind racing. Most of all, like last week’s post on Saturnalia’s vineyard satellite data, I’m totally psyched that these initiatives are live and solid and fertile ground for much more creative thinking about how data can help improve our industry.

CAPTION: The image above shows Saturnalia’s zoomed-out map of two villages in the Champagne region of France: Bouzy and Ambonnay. Click on any of those parcels of vineyard, and you’re “zoomed in” to variables such as vegetation activity, sun exposure and vigor.

Something I love most about Enolytics are the inquiries we see from other companies, usually startups from outside our industry, who have developed a very cool offering and are looking to see if there’s an application to wine.

I love it because it’s bound to be outside-the-box thinking, and because this kind of creativity is finding its way into wine.

One of the hottest sectors lately in this regard?

Satellites.

Or what’s sometimes called “earth observation technologies.”

Normally this technology is put to use for things like street-level image analysis or image object detection or passive crowdsourcing of information.

So what does it have to do with wine?

It can be applied to crop monitoring, for starters, and chemical analysis after harvest, and quality prediction, all based on data gathered by satellites a few kilometers above us. Last week I sat alongside a venture capitalist at the Tech + Fine Wine breakout session during the Fine Minds 4 Fine Wine conference in Champagne and he's already "bought in" to satellite technology.

Which brings me back to real-world applications for the wine industry.

A few months ago we heard from a company doing this kind of work and we asked them for a demonstration of their capabilities. The company is called Ticinum Aerospace, they’re based in Pavia, near Milan, Italy, and they’ve been winning awards in Europe for their innovations. They are working on a corporate project called Saturnalia, which does exactly what's described above.

As an experiment, they offered to study satellite data analysis of specific vineyard sites in the Champagne region of France, so that we could correlate their satellite data about things like vigor, elevation and grape size with our consumer data about things like ratings, sentiment and price of wines from exactly that same area.

Cool idea, right?

My first thought was about studying consumer responses to vineyard-designated wines, compared to consumer responses to wines sourced from less specific locations. What can the data tell us – satellite data compiled together with consumer data, that is – about whether consumers care if a wine comes from a particular place on the earth?

We're still working through some of this but here's what we know so far, according to Daniele De Vecchi PhD, CTO of Ticinum:

The final taste of wine depends on several variables, but space-based monitoring of vineyards plus in-situ recording of environmental conditions goes a long way in predicting how it will perform.

Existing weather stations are good, but innovation could take them a step further; Ticinum’s innovative, patent-based weather station is a bit cheaper and a bit smarter than its predecessors, which is a benefit of the wine production chain link by link.

Wine tasters and critics do not need to worry about their jobs, but objective wine characterization provides a long-awaited, neutral reference for vendors and buyers alike.

How do these takeaways relate to consumer behavior around the wines produced from these very same vineyards?

That’s what we’ll be exploring in the coming weeks. Please stay tuned, and of course be in touch with any questions or comments in the meantime.

But there's been some really cool -- and, to me, inspiring -- amount of information buzzing around about data for the wine industry.

This week I'd like to turn your attention to articles and posts that have particularly caught my attention, because they've been generated from within this community of people who are interested and engaged in the topic of wine and data.

If you're reading this, you're part of the community too.

If you haven't seen these posts, or if these companies aren't yet on your radar for their work, I hope they will be. Because they're contributing and thinking and sharing valuable insights, for the betterment of the industry.

That's why I'm inspired. I hope you will be too.

[Sidebar: We’re hitting the road this weekend, and looking forward very much to participating in the Fine Minds 4 Fine Wine conference in Champagne, France. For those of you in the US, enjoy your Fourth of July celebrations! We’ll see you back here in two weeks.]

What we’re trying to do at Enolytics is unfamiliar, so it’s natural that we hear lots of questions and even our fair share of skepticism.

I hear you. And we’ve figured out how to respond, step by step.

Step One: Trust in the Relationship

We’re all business people and, especially with a new and unfamiliar initiative, we need to protect what we have. Legally, this usually means signing an NDA. We want you to feel comfortable that your data is yours, that it is safe, and that we will only use it for your purposes and for a particular project we define together.

Step Two: Start Small

Not “small” in terms of ideas or goals, but small in terms of actual data. Yes, Enolytics is all about big data but big data is all about tiny bits of information. That’s why, in the earliest stages of working with both clients and data partners, we ask for samples. Small, representative samples, that is, of their bigger data picture.

With winery clients, that usually means a csv file that’s a slice of their DTC database. With data partners, that usually means a spreadsheet of fields they collect.

This addresses the most common question we hear – “Where do we even start?” – and makes it doable.

Step Three: Prototype

This is where it gets real, because we now know what we’re dealing with as we work to build a solution, and you start to see how that solution is going to look.

It’s like building the framework. Again, step by step, and it all started with that small sample.

***

Does that make sense? Are you ready to take your first step? Let us talk you through it.

Do you treat the millennial customers in your DTC program differently than, say, your baby boomers?

Do you segment them by gender and location?

Have you identified spend patterns and varietal preferences, in order to customize your offerings to best suit their profile?

I'll be totally psyched for you if you do.

It would be an excellent application of analyzing data that you already own, and you'd be a few steps ahead of some wineries we've been talking to these past few weeks.

You'd also be in the minority, in terms of maximizing your own data and in terms of communicating with millennials.

How to do both of those things are questions that have come up for Enolytics again and again. We're gaining traction when it comes to helping wineries more strategically utilize their customer data (including data about millennials) and this week I'd like to share some strategies about the second question.

How can we do a better job of reaching millennial wine consumers? And how can we sell them more wine?

For a perspective on this, I'd like to welcome a guest contributor to Enolytics 101. Olivia Schonewise, a colleague and friend who I've come to know in the past year or so, piqued my interest because of her experience and intelligence, and also for her candor about the wine industry's lag in reaching the millennial demographic of which she is a part.

I invited Olivia to speak to what we're doing wrong and, more importantly, how we can do better. Here are four things she'd like us all to know, followed by her ten suggestions that wineries can execute straight away.

Here she is.

* * *

What the Wine Industry Needs to Hear about Millennial Consumers

The wine industry doesn't understand consumers in their 20's, which is amusing because we are literally the most transparent generation of people in history.

There are lots of questions being asked about millennials, like who we are, what we want, and how to get us to buy wine. There aren't a lot of good answers yet, probably because the people trying to answer the questions are not, in fact, millennials.

Wine brands are not meeting millennial consumers where we are. That, in a nutshell, is the disconnect between millennials and the wine industry.

If you’re unsure of where to start, think like a millennial. Or better yet, hire a millennial. No one understands millennials better than millennials themselves.

What Wine Brands Can Do Right Now

Meet us on the interfaces and platforms we're using, not the ones that the wine industry has used in the past.

This means Instagram.

It also means lifestyle websites. (See numbers 8 to 10, below.)

Instagram again: The wine industry prides itself on creating products with stories and connections that feel very personal to consumers. Instagram allows wineries to communicate directly with the people who buy and consume their products, and that’s about as personal as it gets.

I genuinely believe that Instagram is the most untapped marketing resource of the wine industry, and the lack of brands who are active on it is astonishing. There are over 800 million active Instagram users, and more than 50% of them are millennials (aged 22 to 37).

You don't have to have a huge budget. You just have to be present.

Post, comment and engage daily. Give your customers a platform to learn more about your products while creating a community.

LIfestyle websites are like our modern day newspapers and magazines. These include Brit + Co, BuzzFeed, Popsugar, Mashable, Business Insider, Refinery29 and many more. This is where millennials stay up to date on world events, learn about new products, discover trends, and share information. It’s how we digitally "hang out."

This week I’d like to show you a picture. A screenshot, actually, of something we’ve been working on.

What you see above is a visualization of the words that consumers use most frequently to describe one of our clients’ wines. The bigger the word, the more often it’s been used.

It's like listening in on what consumers are saying about your wine.

This visualization is in German, obviously, and we’ve done this type of work in Italian and English as well, in response to the demands of our clients who want to get a ground-level understanding of how everyday consumers in different countries actually speak about their wines.

This isn’t how winemakers speak, and it isn’t how marketers speak most of the time. These are the words of consumers – the people who actually buy your wine – which our clients use to “meet consumers where they are” as they revise the word choices of their communications.

Want to convince people to buy your wine over your competitors'? Speak their own language.

Our client’s sales staff – around Europe, in this case – are now better equipped and better prepared to do exactly that. To speak to consumers in words that are already familiar and commonplace in their everyday wine experiences.

Enolytics is built to address the blindspots of wine consumer behavior. There shouldn’t BE blindspots in the first place, not with all of the technology and digital trails at our fingertips today. But there are, and we’re putting the power of data analysis to use in order to alleviate the problem.

You don’t need to understand the nuts and bolts of how we arrived at a visualization like this. (That’s the work and expertise of our data team, and they amaze me every single day.) What you need are precise tools and information that help you reach consumers better, and sell more wine.

They can be anywhere in the world, and they can be at home or in a restaurant or standing in the aisle of a retail outlet. The point is that this is where the data starts: with one person.

That one person has bought a wine, and they’re engaging some digital platform in order to document it for themselves or to share it with their friends. Those moments are when the data scale begins to tip, because that one person joins the chain of wine consumer behavior that is very quickly hundreds of links long.

Soon, simply because wine is dynamic and interactive and so too is the digital nature of things, those links multiply – to thousands, to hundreds of thousands, to millions, to hundreds of millions…

To billions.

That scale is where we find ourselves this week.

In other words, neck deep.

This week we’ve been working on a project in Europe. It involves several data sources and over 10 million records, just for starters.

Here’s one of the things that we want to do with that data: analyze consumer sentiment, which means breaking down user reviews into terms – each one a link in the wine consumer chain – that are analyzable algorithmically.

They’re words that an everyday consumer, your end consumer, uses to describe your wine. When each of their words in a consumer review is a data point, it’s also a new link in the chain we’re analyzing.

It’s about turning unstructured data (free text) into structured data. Some people call it natural-language processing (NLP) – a branch of Artificial Intelligence (AI), which looks for the meaning of what consumers are saying and convert it to structured, mine-able data.

Let’s say that the 10 million records we’re starting with each contains a modest 10-word review. That’s 100 million data points.

When those words are in three different languages – English, German and Italian, in this case – the number of data points expands by another factor.

As of this writing, we’re processing more than one half of a billion (500,000,000) data records, and that’s just with one project.

The result is that we can confidently link the consumer sentiment, in their own words, to specific wines, brands, regions, varietals, and competitors. The number of data points continues to expand, and expand some more.

As I said, we’re neck deep.

We’ve had to make some adjustments, structurally speaking.

We had to enhance our infrastructure. We had to switch over to what’s called a data lake, which is a storage repository that holds a vast amount of raw data in its native format. And we’re harnessing the power of machine learning to do what we need to do to fulfill our promise to our clients.

Big data is big, right? But what we all need to remember is that it begins and ends with that one single consumer who’s buying and drinking your wine.

If he’s true to form, as I expect he will be, Richard won’t be letting any of us off easy. That is, he’ll be holding us accountable – Jonathan, to explain the best ways to use data throughout the supply chain; Jon, to demonstrate the practical uses of blockchain technology and cryptocurrencies for the wine industry; and me, to illustrate applications of big data around consumer behavior and insights.

We won’t be the first or the only ones to engage this question. At last December’s wine2wine conference in Verona, for example, Paul Mabray moderated a session that featured Paul Howard speaking about blockchain for wine.

It was barely five months ago, and already I feel like there are new things to say. The subject is that dynamic.

It’s why these sessions are so important, IMO. One builds on another. Each pushes the envelope a bit further. And every time there are questions. Questions of clarification. Questions about How do I…? Questions where the answers need to address what all of this technology means to the people in the audience in particular, and to the wine business in general.

That’s what I’ll be listening for, and looking to learn. It’s what I’m committed to bringing home, sharing with you, and making real for our clients.

Please stay tuned, and stay in touch. As always, I welcome your questions and suggestions and comments.

They're some of the most important "assets" that a new venture can have.

They're the people who *get* what you're trying to do before anyone else does.

They're the ones who are willing to say, We don't exactly know how this is going to help, but we want to figure it out.

They're also the ones who are willing to speak up, who have the temerity to raise their hand first and say that there's value in the new idea.

Dry Creek Vineyard, and especially Michael Longerbeam, their DTC Manager, have been all of those things for us, almost from the very beginning of Enolytics two years ago.

Michael and his work at Dry Creek are featured this month in Wines & Vines magazine, in an article by Andy Starr called "How Wineries Take Advantage of Big Data," and we couldn't be happier to see him getting the recognition he deserves. (Screenshot from the online version is above.)

Enolytics is in the article too, in the context of providing something that every winery should have: a breakout of their wine portfolio by margin and volume, displayed in an easy-to-understand graphic.

It's what Michael first asked us to do with Dry Creek's data, and it's been a cornerstone of our work ever since. Please let us know if we can do the same for you.

It may not be on your radar yet, mainly because it’s based in British Columbia.

But here’s what’s important for the audience of this Enolytics 101 series to know about Quini: they use real-time data, in the form of wine consumer sensory and attitudinal feedback, to deliver personalized and actionable insights that a retailer, wine producer or large restaurant company can use immediately.

Here’s how it works. I’ll use the retail sales environment as an example.

Introduction: A store offers their customers a smart, fast way to search for wine they will likely enjoy, on their website or in store on the customer’s smartphone, powered by Quini.

Execution: Customers provide feedback on the Quini app about the wines they taste, whether at in-person tastings, at home, virtual wine club events or any other opportunity.

Backend: The app records between 30 and 40 data points about any given wine, about descriptors like aromas and tannins but also about variables such as expectations and likeability.

Bonus: Staff can also input their own feedback about the wine, as well as food pairings and other notes that are unique to the store.

The retailer is able to see that feedback in real time. Which means that the retailer can pull up the customer’s profile – while they’re standing in the store or when the retailer is putting together their next wine club shipment – and see that, for example, the customer has tried a few chardonnays that don’t seem to be jiving with their palate.

The retailer can then recommend different wines that steer away from what the customer didn’t like about the chardonnays, and focus more on specific wine, categories and types they did enjoy.

On their dashboard, the retailer can also spot wines the customer may have tried somewhere else and take action to be first in the area to bring it in – or offer to the customer a similar wine.

In a nutshell, retailers can automate their ability to service their customers like never before, using data.

“This helps to go from being a traditional retailer to a more intelligence-based organization,” said Roger Noujeim, CEO of Quini.

That’s why Quini is now on your radar.

Note: They’re based in British Columbia but the platform is usable in the US and worldwide, in winery, retail and restaurant environments.

Why am I telling you about this?

Because it's way cool for anyone interested in wine and data.

Because we respect its technology and execution.

Because it's powerful enough on its own, which also makes it exceptionally helpful as a data partner in our ecosystem, particularly when aggregated with complementary sources.

Please be in touch with any comments or ideas, and thank you, as always, for reading.